Process Mining on Uncertain Event Data

TL;DR

This paper explores developing process mining techniques tailored for uncertain event data, which contain imprecise attributes, aiming to enhance analysis capabilities for non-standard, uncertain datasets in process science.

Contribution

It establishes foundational methods and a research agenda for process mining on uncertain data, addressing a gap in current techniques.

Findings

Literature review of existing approaches

Framework for process mining on uncertain data

Identification of future research directions

Abstract

With the widespread adoption of process mining in organizations, the field of process science is seeing an increase in the demand for ad-hoc analysis techniques of non-standard event data. An example of such data are uncertain event data: events characterized by a described and quantified attribute imprecision. This paper outlines a research project aimed at developing process mining techniques able to extract insights from uncertain data. We set the basis for this research topic, recapitulate the available literature, and define a future outlook.